Results 91 to 100 of about 64,803 (263)
Periprosthetic joint infection establishes a sophisticated immunosuppressive network between CXCR4+ PMN‐MDSCs and Bregs, inducing profound CD8+ T cell paralysis. Alendronate effectively disrupts this CXCR4+ PMN‐MDSC–Breg axis by targeting STAT3, thereby restoring local immune surveillance.
Jintao Wu +9 more
wiley +1 more source
Updatable Closed‐Form Evaluation of Arbitrarily Complex Multiport Network Connections
The inverse design of electrically large wave devices often uses reduced‐order multiport models with discrete optimization, requiring many evaluations of complex interconnections between subsystems that differ only in a few blocks. This paper introduces a closed‐form framework enabling efficient Woodbury low‐rank updates of related, previous ...
Hugo Prod'homme, Philipp del Hougne
wiley +1 more source
Objective. The study sought to examine the progress of teaching library and information science in several Jordanian universities from their establishment till the present (1921–2022).
SERHAN A. AL TAWALBEH +2 more
doaj +1 more source
This meta‐analysis of 208 cases shows that salvage esophagectomy for cT4 esophageal squamous cell carcinoma achieves a 72% R0 resection rate, offering a curative pathway for selected patients. However, it remains a high‐risk procedure with an 18% anastomotic leak rate and 30% major complications (Clavien–Dindo ≥ III).
Makoto Sakai +4 more
wiley +1 more source
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia +3 more
wiley +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley +1 more source
Two‐photon polymerization enables high‐resolution microfabrication, but performing alignment when printing multiple structures is difficult. Here, we present a fast, robust, and open‐source protocol for automated alignment on Nanoscribe systems. Achieving ≈0.4 μm accuracy in under 5 s, our protocol reduces time and error in multimaterial printing. This
Daniel Maher +4 more
wiley +1 more source
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury +4 more
wiley +1 more source
An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto +5 more
wiley +1 more source

